Uniform Attenuation Correction Research Articles

No impact of attenuation and scatter correction on the interpretation of dopamine transporter SPECT in patients with clinically uncertain parkinsonian syndrome

PurposeThe benefit from attenuation and scatter correction (ASC) of dopamine transporter (DAT)-SPECT for the detection of nigrostriatal degeneration in clinical routine is still a matter of debate. The current study evaluated the impact of ASC on visual interpretation and semi-quantitative analysis of DAT-SPECT in a large patient sample.MethodsOne thousand seven hundred forty consecutive DAT-SPECT with 123I-FP-CIT from clinical routine were included retrospectively. SPECT images were reconstructed iteratively without and with ASC. Attenuation correction was based on uniform attenuation maps, scatter correction on simulation. All SPECT images were categorized with respect to the presence versus the absence of Parkinson-typical reduction of striatal 123I-FP-CIT uptake by three independent readers. Image reading was performed twice to assess intra-reader variability. The specific 123I-FP-CIT binding ratio (SBR) was used for automatic categorization, separately with and without ASC.ResultsThe mean proportion of cases with discrepant categorization by the same reader between the two reading sessions was practically the same without and with ASC, about 2.2%. The proportion of DAT-SPECT with discrepant categorization without versus with ASC by the same reader was 1.66% ± 0.50% (1.09–1.95%), not exceeding the benchmark of 2.2% from intra-reader variability. This also applied to automatic categorization of the DAT-SPECT images based on the putamen SBR (1.78% discrepant cases between without versus with ASC).ConclusionGiven the large sample size, the current findings provide strong evidence against a relevant impact of ASC with uniform attenuation and simulation-based scatter correction on the clinical utility of DAT-SPECT to detect nigrostriatal degeneration in patients with clinically uncertain parkinsonian syndrome.

Attenuation correction using deep learning for brain perfusion SPECT images

Non-uniform attenuation correction using computed tomography (CT) improves the image quality and quantification of single-photon emission computed tomography (SPECT). However, it is not widely used because it requires a SPECT/CT scanner. This study constructs a convolutional neural network (CNN) to generate attenuation-corrected SPECT images directly from non-attenuation-corrected SPECT images. We constructed an auto-encoder (AE) using a CNN to correct the attenuation in brain perfusion SPECT images. SPECT image datasets of 270 (44,528 slices including augmentation), 60 (5002 slices), and 30 (2558 slices) cases were used for training, validation, and testing, respectively. The acquired projection data were reconstructed in three patterns: uniform attenuation correction using Chang's method (Chang-AC), non-uniform attenuation correction using CT (CT-AC), and no attenuation correction (No-AC). The AE learned an end-to-end mapping between the No-AC and CT-AC images. The No-AC images in the test dataset were loaded into the trained AE, which generated images simulating the CT-AC images as output. The generated SPECT images were employed as attenuation-corrected images using the AE (AE-AC). The accuracy of the AE-AC images was evaluated in terms of the peak signal-to-noise ratio (PSNR) and the structural similarity metric (SSIM). The intensities of the AE-AC and CT-AC images were compared by voxel-by-voxel and region-by-region analysis. The PSNRs of the AE-AC and Chang-AC images, compared using CT-AC images, were 62.2, and 57.9, and their SSIM values were 0.9995 and 0.9985, respectively. The AE-AC and CT-AC images were visually and statistically in good agreement. The proposed AE-AC method yields highly accurate attenuation-corrected brain perfusion SPECT images.

Bone SPECT-based segmented attenuation correction for quantitative analysis of bone metastasis (B-SAC): comparison with CT-based attenuation correction

BackgroundEvidence has shown the clinical usefulness of measuring the metastatic tumor burden of bone for prognostic assessment especially in prostate cancer; quantitative evaluation by dedicated SPECT is difficult due to the lack of attenuation correction (AC) method.We developed a novel method for attenuation correction using bone SPECT emission data (bone SPECT-based segmented attenuation correction; B-SAC) where emission data were virtually segmented into three tissues (i.e., bone, soft tissue, and air). Then, the pixel values in SPECT were replaced by 50 for the virtual soft tissue, and − 1000 for the virtual air. The replaced pixel values for the virtual bone were based on the averaged CT values of the normal vertebrae (B-SACN) or the metastatic bones (B-SACM). Subsequently, the processed SPECT data (i.e., SPECT value) were supposed to realize CT data (i.e., CT value) that were used for B-SAC. The standardized uptake values (SUVs) of 112 metastatic bone tumors in 15 patients with prostate cancer were compared between CTAC with scatter correction (SC) and resolution recovery (RR) and the following reconstruction conditions: B-SACN (+)SC(+)RR(+), B-SACM (+)SC(+)RR(+), uniform AC(UAC)(+)SC(+)RR(+), AC(−)SC(+)RR(+), and no correction (NC).ResultsThe SUVs in the five reconstruction conditions were all correlated with those in CTAC(+)SC(+)RR(+) (p < 0.01), and the correlations between B-SACN or B-SACM and CTAC images were excellent (r > 0.94). Bland-Altman analysis showed that the mean SUV differences between CTAC (+)SC(+)RR(+) and the other five reconstructions were 0.85 ± 2.25 for B-SACN (+)SC(+)RR(+), 1.61 ± 2.36 for B-SACM (+)SC(+)RR(+), 1.54 ± 3.84 for UAC(+)SC(+)RR(+), − 3.12 ± 4.97 for AC(−)SC(+)RR(+), and − 5.96 ± 4.59 for NC. Compared to CTAC(+)SC(+)RR(+), B-SACN (+)SC(+)RR(+) showed a slight but constant overestimation (approximately 17%) of the metastatic tumor burden of bone when the same threshold of metabolic tumor volume was used.ConclusionsThe results of this preliminary study suggest the potential for B-SAC to improve the quantitation of bone metastases in bone SPECT when X-ray CT or transmission CT data are not available. Considering the small but unignorable differences of lesional SUVs between CTAC and B-SAC, SUVs obtained with the current version of B-SAC seem difficult to be directly compared with those obtained with CTAC.

CT-Based Attenuation Correction in Brain SPECT/CT Can Improve the Lesion Detectability of Voxel-Based Statistical Analyses.

BackgroundIntegrated SPECT/CT enables non-uniform attenuation correction (AC) using built-in CT instead of the conventional uniform AC. The effect of CT-based AC on voxel-based statistical analyses of brain SPECT findings has not yet been clarified. Here, we assessed differences in the detectability of regional cerebral blood flow (CBF) reduction using SPECT voxel-based statistical analyses based on the two types of AC methods.Subjects and MethodsN-isopropyl-p-[123I]iodoamphetamine (IMP) CBF SPECT images were acquired for all the subjects and were reconstructed using 3D-OSEM with two different AC methods: Chang’s method (Chang’s AC) and the CT-based AC method. A normal database was constructed for the analysis using SPECT findings obtained for 25 healthy normal volunteers. Voxel-based Z-statistics were also calculated for SPECT findings obtained for 15 patients with chronic cerebral infarctions and 10 normal subjects. We assumed that an analysis with a higher specificity would likely produce a lower mean absolute Z-score for normal brain tissue, and a more sensitive voxel-based statistical analysis would likely produce a higher absolute Z-score for in old infarct lesions, where the CBF was severely decreased.ResultsThe inter-subject variation in the voxel values in the normal database was lower using CT-based AC, compared with Chang’s AC, for most of the brain regions. The absolute Z-score indicating a SPECT count reduction in infarct lesions was also significantly higher in the images reconstructed using CT-based AC, compared with Chang’s AC (P = 0.003). The mean absolute value of the Z-score in the 10 intact brains was significantly lower in the images reconstructed using CT-based AC than in those reconstructed using Chang’s AC (P = 0.005).ConclusionsNon-uniform CT-based AC by integrated SPECT/CT significantly improved sensitivity and the specificity of the voxel-based statistical analyses for regional SPECT count reductions, compared with conventional uniform Chang's AC.

CT-based attenuation and scatter correction compared with uniform attenuation correction in brain perfusion SPECT imaging for dementia

This study investigated if the appearance and diagnostic accuracy of HMPAO brain perfusion SPECT images could be improved by using CT-based attenuation and scatter correction compared with the uniform attenuation correction method.A cohort of subjects who were clinically categorized as Alzheimer’s Disease (), Dementia with Lewy Bodies () or healthy normal controls (), underwent SPECT imaging with Tc-99m HMPAO and a separate CT scan. The SPECT images were processed using: (a) correction map derived from the subject’s CT scan or (b) the Chang uniform approximation for correction or (c) no attenuation correction. Images were visually inspected. The ratios between key regions of interest known to be affected or spared in each condition were calculated for each correction method, and the differences between these ratios were evaluated.The images produced using the different corrections were noted to be visually different. However, ROI analysis found similar statistically significant differences between control and dementia groups and between AD and DLB groups regardless of the correction map used.We did not identify an improvement in diagnostic accuracy in images which were corrected using CT-based attenuation and scatter correction, compared with those corrected using a uniform correction map.

Influences of reconstruction and attenuation correction in brain SPECT images obtained by the hybrid SPECT/CT device: evaluation with a 3-dimensional brain phantom.

The aim of this study was to evaluate the influences of reconstruction and attenuation correction on the differences in the radioactivity distributions in (123)I brain SPECT obtained by the hybrid SPECT/CT device. We used the 3-dimensional (3D) brain phantom, which imitates the precise structure of gray matter, white matter and bone regions. It was filled with (123)I solution (20.1 kBq/mL) in the gray matter region and with K2HPO4 in the bone region. The SPECT/CT data were acquired by the hybrid SPECT/CT device. SPECT images were reconstructed by using filtered back projection with uniform attenuation correction (FBP-uAC), 3D ordered-subsets expectation-maximization with uniform AC (3D-OSEM-uAC) and 3D OSEM with CT-based non-uniform AC (3D-OSEM-CTAC). We evaluated the differences in the radioactivity distributions among these reconstruction methods using a 3D digital phantom, which was developed from CT images of the 3D brain phantom, as a reference. The normalized mean square error (NMSE) and regional radioactivity were calculated to evaluate the similarity of SPECT images to the 3D digital phantom. The NMSE values were 0.0811 in FBP-uAC, 0.0914 in 3D-OSEM-uAC and 0.0766 in 3D-OSEM-CTAC. The regional radioactivity of FBP-uAC was 11.5% lower in the middle cerebral artery territory, and that of 3D-OSEM-uAC was 5.8% higher in the anterior cerebral artery territory, compared with the digital phantom. On the other hand, that of 3D-OSEM-CTAC was 1.8% lower in all brain areas. By using the hybrid SPECT/CT device, the brain SPECT reconstructed by 3D-OSEM with CT attenuation correction can provide an accurate assessment of the distribution of brain radioactivity.

Impact of CT attenuation correction by SPECT/CT in brain perfusion images

The aim of this study was to elucidate the regional differences between brain perfusion single photon emission computed tomography (SPECT) images reconstructed with a uniform attenuation correction using Chang's method (AC-Chang) and a non-uniform attenuation correction with CT using SPECT/CT (AC-CT). SPECT images of a phantom with and without head holder were obtained, and reconstructed images of AC-Chang and AC-CT were compared. Twenty-eight consecutive patients with brain disease examined by SPECT/CT brain perfusion imaging were selected, and images were reconstructed with AC-Chang and AC-CT. The AC-Chang and AC-CT reconstructed images were then compared by voxel-based analysis using three-dimensional stereotactic surface projections. Counts in the frontal area of the AC-Chang phantom image with head holder were higher than those in the posterior area. Counts in the frontal area of the AC-Chang clinical images were significantly higher than those in the AC-CT images, while the counts in the margin of the frontal lobe and posterior margin of the parietal, occipital cortices and cerebellum of the AC-Chang images were significantly lower. Relative frontal perfusion was 5.0% higher and relative cerebellar perfusion was 4.6% lower in the AC-Chang images relative to the AC-CT images, on average. We demonstrated the frontal dominant hyper-perfusion and parieto-occipital and cerebellar hypo-perfusion in brain SPECT images reconstructed with AC-Chang compared to those reconstructed with AC-CT. We suggest that to obtain an accurate attenuation-corrected brain perfusion SPECT image, attenuation correction by Chang's method is inadequate.

Quantitative multi-pinhole small-animal SPECT: uniform versus non-uniform Chang attenuation correction

Attenuation of photon flux on trajectories between the source and pinhole apertures affects the quantitative accuracy of reconstructed single-photon emission computed tomography (SPECT) images. We propose a Chang-based non-uniform attenuation correction (NUA-CT) for small-animal SPECT/CT with focusing pinhole collimation, and compare the quantitative accuracy with uniform Chang correction based on (i) body outlines extracted from x-ray CT (UA-CT) and (ii) on hand drawn body contours on the images obtained with three integrated optical cameras (UA-BC). Measurements in phantoms and rats containing known activities of isotopes were conducted for evaluation. In 125I, 201Tl, 99mTc and 111In phantom experiments, average relative errors comparing to the gold standards measured in a dose calibrator were reduced to 5.5%, 6.8%, 4.9% and 2.8%, respectively, with NUA-CT. In animal studies, these errors were 2.1%, 3.3%, 2.0% and 2.0%, respectively. Differences in accuracy on average between results of NUA-CT, UA-CT and UA-BC were less than 2.3% in phantom studies and 3.1% in animal studies except for 125I (3.6% and 5.1%, respectively). All methods tested provide reasonable attenuation correction and result in high quantitative accuracy. NUA-CT shows superior accuracy except for 125I, where other factors may have more impact on the quantitative accuracy than the selected attenuation correction.

The Role of CT-Based Attenuation Correction and Collimator Blurring Correction in Striatal Spect Quantification

Purpose. Striatal single photon emission computed tomography (SPECT) imaging of the dopaminergic system is becoming increasingly used for clinical and research studies. The question about the value of nonuniform attenuation correction has become more relevant with the increasing availability of hybrid SPECT-CT scanners. In this study, the value of nonuniform attenuation correction and correction for collimator blurring were determined using both phantom data and patient data. Methods. SPECT imaging was performed using 7 anthropomorphic phantom measurements, and 14 patient studies using [I-123]-FP-CIT (DATSCAN). SPECT reconstruction was performed using uniform and nonuniform attenuation correction and collimator blurring corrections. Recovery values (phantom data) or average-specific uptake ratios (patient data) for the different reconstructions were compared at similar noise levels. Results. For the phantom data, improved recovery was found with nonuniform attenuation correction and collimator blurring corrections, with further improvement when performed together. However, for patient data the highest average specific uptake ratio was obtained using collimator blurring correction without nonuniform attenuation correction, probably due to subtle SPECT-CT misregistration. Conclusions. This study suggests that an optimal brain SPECT reconstruction (in terms of the lowest bias) in patients would include a correction for collimator blurring and uniform attenuation correction.

Uniform attenuation correction using the frequency‐distance principle

The frequency-distance principle (FDP) is a well-known relationship that relates the distance between the object and the detector to the slope in the two-dimensional Fourier transform of the projection sinogram. This relationship has been previously applied to compensation of the distance dependent collimator blurring in SPECT (single photon emission computed tomography) in the literature. This paper makes an attempt to use the FDP to correct for uniform attenuation in SPECT. Computer simulations reveal that this technique works well for objects consisting of point sources but does not work well for distributed objects.

Effect of scatter and attenuation correction in ROI analysis of brain perfusion scintigraphy

The AIM of this study was to evaluate the effect of scatter and attenuation correction in region of interest (ROI) analysis of brain perfusion single-photon emission tomography (SPECT), and to assess the influence of selecting the reference area on the calculation of lesion-to-reference count ratios. Data were collected from a brain phantom and ten patients with unilateral internal carotid artery stenosis. A simultaneous emission and transmission scan was performed after injecting 123I-iodoamphetamine. We reconstructed three SPECT images from common projection data: with scatter correction and nonuniform attenuation correction, with scatter correction and uniform attenuation correction, and with uniform attenuation correction applied to data without scatter correction. Regional count ratios were calculated by using four different reference areas (contralateral intact side, ipsilateral cerebellum, whole brain and hemisphere). Scatter correction improved the accuracy of measuring the count ratios in the phantom experiment. It also yielded marked difference in the count ratio in the clinical study when using the cerebellum, whole brain or hemisphere as the reference. Difference between nonuniform and uniform attenuation correction was not significant in the phantom and clinical studies except when the cerebellar reference was used. Calculation of the lesion-to-normal count ratios referring the same site in the contralateral hemisphere was not dependent on the use of scatter correction or transmission scan-based attenuation correction. Scatter correction was indispensable for accurate measurement in most of the ROI analyses. Nonuniform attenuation correction is not necessary when using the reference area other than the cerebellum.

An analytical algorithm for skew-slit collimator SPECT with uniform attenuation correction

To replace the conventional pinhole (normal cone-beam) collimator, a novel skew-slit collimator was previously proposed and a Novikov-type algorithm developed to reconstruct images using the skew-slit geometry. The goal of this paper is to develop a reconstruction algorithm that has better noise control than the Novikov-type algorithm. The new algorithm is able to compensate for uniform attenuation, and computer simulation results show that reconstructed images are less noisy.

The influence of attenuation correction and reconstruction techniques on the detection of hypo-perfused lesions in brain SPECT images

We evaluated the effects of attenuation correction and reconstruction techniques on the detection of hypoperfused lesions in brain SPECT imaging. A software phantom was constructed using the data available on the BrainWeb database by assigning activity values to grey and white matter. The true attenuation map was generated by assigning attenuation coefficients to six different tissue classes to create a non-uniform attenuation map. The uniform attenuation map was calculated using an attenuation coefficient of 0.15 cm(-1). Hypoperfused lesions of varying intensities and sizes were added. The phantom was then projected as typical SPECT projection data, taking into account attenuation and collimator blurring with the addition of Poisson noise. The projection data were reconstructed using four different methods: filtered back-projection in combination with Chang's first-order attenuation correction using the uniform or the true attenuation map and maximum likelihood iterative reconstruction using the uniform or the true attenuation map. Different Gaussian post-smoothing kernels were applied onto the reconstructed images and the performance of each procedure was analysed using figures of merit such as signal-to-noise ratio, bias and variance. Uniform attenuation correction offered only slight deterioration of the signal-to-noise ratio compared to the true attenuation map. Maximum likelihood produced superior signal-to-noise ratios and lower bias at the same variance in comparison to the filtered back-projection. Uniform attenuation correction is adequate for lesion detection while maximum likelihood provides enhanced lesion detection when compared to filtered back-projection.

Exact fan‐beam and ‐acquisition cone‐beam SPECT algorithms with uniform attenuation correction

This paper presents analytical fan‐beam and cone‐beam reconstruction algorithms that compensate for uniform attenuation in single photon emission computed tomography. First, a fan‐beam algorithm is developed by obtaining a relationship between the two‐dimensional (2D) Fourier transform of parallel‐beam projections and fan‐beam projections. Using this relationship, 2D Fourier transforms of equivalent parallel‐beam projection data are obtained from the fan‐beam projection data. Then a quasioptimal analytical reconstruction algorithm for uniformly attenuated Radon data, developed by Metz and Pan, is used to reconstruct the image. A cone‐beam algorithm is developed by extending the fan‐beam algorithm to solid angle geometry. The cone‐beam algorithm is also an exact algorithm.

Influence of photon scattering and attenuation on ROI analysis in brain perfusion single-photon emission tomographic imaging of normal subjects

The aim of this study was to evaluate the effect of scatter and attenuation correction in region of interest (ROI) analysis in brain perfusion single-photon emission tomography (SPECT) and to assess the influence of selecting the reference area on semi-quantification. Ten normal subjects were enrolled and injected with 123I-iodoamphetamine to undergo simultaneous emission and transmission scanning for scatter and attenuation correction. We reconstructed three SPECT images from common projection data of each subject: with scatter correction and non-uniform attenuation correction, with scatter correction and uniform attenuation correction, and with uniform attenuation correction applied to data without scatter correction. A program for automated ROI drawing was used to set ROIs on various regions in brain images. Regional count ratios were compared in images with different correction procedures by using three different reference areas. The effect of the combination of scatter and attenuation correction was marked in the precentral, temporal, posterior, hippocampus and especially in the cerebellum. In contrast, it was not appreciable in the central and parietal areas. When using the cerebellar ROI as the reference, the count ratio varied widely depending on the correction procedures. On the other hand, the whole brain reference offered the least variation in the count ratio. The influence of photon scattering and attenuation was dependent on regions. Since the count in the cerebellar ROI is greatly affected by photon scattering and attenuation, nonuniform attenuation correction combined with scatter correction deserves consideration when using the cerebellar ROI as the reference.

Analytical fan-beam and cone-beam reconstruction algorithms with uniform attenuation correction for SPECT

In this paper, we developed an analytical fan-beam reconstruction algorithm that compensates for uniform attenuation in SPECT. The new fan-beam algorithm is in the form of backprojection first, then filtering, and is mathematically exact. The algorithm is based on three components. The first one is the established generalized central-slice theorem, which relates the 1D Fourier transform of a set of arbitrary data and the 2D Fourier transform of the backprojected image. The second one is the fact that the backprojection of the fan-beam measurements is identical to the backprojection of the parallel measurements of the same object with the same attenuator. The third one is the stable analytical reconstruction algorithm for uniformly attenuated Radon data, developed by Metz and Pan. The fan-beam algorithm is then extended into a cone-beam reconstruction algorithm, where the orbit of the focal point of the cone-beam imaging geometry is a circle. This orbit geometry does not satisfy Tuy's condition and the obtained cone-beam algorithm is an approximation. In the cone-beam algorithm, the cone-beam data are first backprojected into the 3D image volume; then a slice-by-slice filtering is performed. This slice-by-slice filtering procedure is identical to that of the fan-beam algorithm. Both the fan-beam and cone-beam algorithms are efficient, and computer simulations are presented. The new cone-beam algorithm is compared with Bronnikov's cone-beam algorithm, and it is shown to have better performance with noisy projections.

Assessment of quantitative SPECT 99mTc labelled white cell scans to monitor response to treatment of inflammatory bowel disease

Aim To assess the efficacy of repeat quantitative SPECT white cell scans (WCSs) for assessing response to therapy in patients with active inflammatory bowel disease (IBD). It has been shown that quantitative SPECT WCSs correlate very well with histology, the recognized ‘gold standard’ for assessing the severity of IBD. Methods The final study group consisted of 21 subjects with active IBD. SPECT 99mTc labelled white cell scans were performed immediately prior to and 2 weeks after initiation of anti-inflammatory treatment. Image processing was performed by 2 observers blinded to the identity of the subjects. Uniform attenuation correction was applied. SPECT scores (the ratio of the maximal bowel uptake to that of the hottest vertebral bone marrow segment) were obtained for ‘pre’ scans and repeated for the same bowel segment in ‘post’ scans. Results SPECT scores were recorded in the range of approximately 0–7 and correlation between observers for repeat SPECT scores was good (r2=0.87). Two of 23 (9%) decreased, 6/23 (28%) showed little change and 15/23 (65%) improved with a range of SPECT score differences of up to 3. Conclusion We have shown that the use of repeat quantitative SPECT WCSs is a reproducible method that may be used to assess the direction and magnitude of the response to treatment.

Detection of lung cancer with positron coincidence gamma camera using fluorodeoxyglucose in comparison with dedicated PET

Objective: Dual-head gamma cameras with sodium iodide (NaI) detectors operated in coincidence mode provide a new approach for imaging with positron-labeled tracers. The purpose of this study was to evaluate the feasibility of FDG imaging with positron coincidence detection gamma camera (PCD) in detecting lung tumor in comparison with FDG imaging with the dedicated positron emission tomography (PET). Methods and material: Twenty-six lesions of 13 patients with suspected lung cancer were studied with both FDG PET and FDG PCD on the same day. Pulmonary lesions were analyzed visually and semi-quantitatively using the ratio of target-to-background counts (T/B ratio). Results and conclusions: FDG PCD and FDG PET could detect visually 21 lesions (80.8%) and 23 lesions (88.0%), respectively. The mean T/B ratio and standard deviation (S.D.) of FDG PCD was 4.6±3.9, significantly lower than that of FDG PET (11.4±6.6, P<0.001). When pulmonary lesions were no more than 2.0 cm in diameter, the sensitivity of FDG PCD was 37.5%, significantly inferior to that of FDG PET (62.5%, P<0.001). There was no statistically significant difference of the sensitivity between the FDG PCD and FDG PET in lesions of more than 2.0 cm in diameter. FDG PCD with uniform attenuation correction was clinically available in detecting lung cancer. However, the sensitivity for small lesions less than 2.0 cm was limited. The application of measured attenuation correction and scatter correction may to be needed to improve the detectability of FDG PCD, especially for detecting small lung cancer.

Regional brain perfusion in 10 normal dogs measured using Technetium-99m ethyl cysteinate dimer spect.

Single photon emission computed tomography (SPECT) of the brain using perfusion tracers allows estimation of regional brain perfusion. This allows in vivo examination of brain function in the setting of neuropsychologic and pathophysiologic changes. However functional imaging data on brain perfusion in dogs are limited. Hence, the aim of this study was to determine the scintigraphic regional perfusion pattern of the normal canine brain. Ten healthy shepherd type dogs were injected with 925 MBq Technetium-99m ethyl cysteinate (ECD) 20 minutes before the examination. Acquisition was performed using a triple head gamma camera equipped with fanbeam collimators. Uniform attenuation correction and triple energy window correction were applied. Computed tomographic images were obtained from the same dogs, reoriented along the orbito-meatal axis and SPECT perfusion data were coregistered to the CT-volume data. Based on morphological and suggested brain divisions, regions-of-interest (ROIs) were defined for the bilateral frontocerebral, temporocerebral, parietocerebral, occipitocerebral, cerebellar, thalamic, and striatal area. Regional count density was normalized on total counts. All dogs had the highest uptake in the thalamic/striatal area compared to a rather homogeneous cerebral uptake. No significant left/right count differences were found, but a rostro-caudal gradient (+12-13%) was present. In this group, age and gender did not influence the perfusion pattern.

Transfer of normal 99mTc-ECD brain SPET databases between different gamma cameras.

A stereotactic, normal perfusion database is imperative for optimal clinical brain single-photon emission tomography (SPET). However, interdepartmental use of normal data necessitates accurate transferability of these data sets. The aim of this study was to investigate transfer of three normal perfusion databases obtained in the same large population of healthy volunteers who underwent sequential scanning using multihead gamma cameras with different resolution. Eighty-nine healthy adults (46 females, 43 males; aged 20-81 years) were thoroughly screened by history, biochemistry, physical and full neurological examination, neuropsychological testing and magnetic resonance imaging. After injection of 925 MBq technetium-99m labelled ethyl cysteinate dimer (ECD) under standard conditions, 101 scans were acquired from all subjects (12 repeat studies) on a triple-head Toshiba GCA-9300A (measured average FWHM 8.1 mm). Ninety-one sequential scans were performed on a dual-head Elscint Helix camera (FWHM 9.6 mm) and 22 subjects also underwent imaging on a triple-head Prism 3000 (FWHM 9.6 mm). Images were transferred to the same processing platform and reconstructed by filtered back-projection with the same Butterworth filter (order 8, cut-off 0.9 cycles/cm) and uniform Sorensen attenuation correction (mu = 0.09). After automated rigid intrasubject registration, all subjects were automatically reoriented to a stereotactic template by a nine-parameter affine transformation. The databases were analysed using 35 predefined volumes of interest (VOIs) with normalisation on total VOI counts. For comparison, the high-resolution data were smoothed with a 3D Gaussian kernel to achieve more similar spatial resolution. Hoffman phantom measurements were conducted on all cameras. Partial volume effects after smoothing varied between -6.5% and 10%, depending on VOI size. Between-camera reproducibility was 2.5% and 2.7% for the Toshiba camera versus the Helix and the Prism database, respectively. The highest reduction in between-camera variability was achieved by resolution adjustment in combination with linear washout correction and a Hoffman phantom-based correction. In conclusion, transfer of normal perfusion data between multihead gamma cameras can be accurately achieved, thereby enabling widespread interdepartmental use, which is likely to have a positive impact on the diagnostic capabilities of clinical brain perfusion SPET.